This paper is in the following e-collection/theme issue:

Patient-Reported Outcome Measures (PROMs) (275) Decision Support for Health Professionals (1145) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (147) Machine Learning (1400)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42384, first published .
Psychometric Properties of a Machine Learning–Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study

Psychometric Properties of a Machine Learning–Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study

Psychometric Properties of a Machine Learning–Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study

Authors of this article:

Virginie Korb-Savoldelli1, 2 Author Orcid Image ;   Yohann Tran3, 4 Author Orcid Image ;   Germain Perrin1, 5 Author Orcid Image ;   Justine Touchard1 Author Orcid Image ;   Jean Pastre6 Author Orcid Image ;   Adrien Borowik1 Author Orcid Image ;   Corine Schwartz1 Author Orcid Image ;   Aymeric Chastel1 Author Orcid Image ;   Eric Thervet7, 8 Author Orcid Image ;   Michel Azizi4, 9 Author Orcid Image ;   Laurence Amar4, 9 Author Orcid Image ;   Benjamin Kably4, 10 Author Orcid Image ;   Armelle Arnoux3, 4, 5 Author Orcid Image ;   Brigitte Sabatier1, 2, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations (6) Metrics

Journals

  1. Van Coillie S, Prévot J, Sánchez-Ramón S, Lowe D, Borg M, Autran B, Segundo G, Pecoraro A, Garcelon N, Boersma C, Silva S, Drabwell J, Quinti I, Meyts I, Ali A, Burns S, van Hagen M, Pergent M, Mahlaoui N. Charting a course for global progress in PIDs by 2030 — proceedings from the IPOPI global multi-stakeholders’ summit (September 2023). Frontiers in Immunology 2024;15 View